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RC TOM Challenge 2018

November 13, 2018

Read The Full Prompt

The TOM Challenge provides an opportunity for you to continue exploring organizational learning and innovation through the lens of process improvement and/or product development, the focus of RC TOM’s second module. In this challenge, you will investigate how an organization is grappling with machine learning, additive manufacturing, or open innovation. These megatrends are likely to significantly affect how organizations manage process improvement and product development in the coming years of your career. The TOM Challenge requires you to (1) conduct research and write an essay that examines how one organization is facing a particular aspect of one of these megatrends, and (2) write six comments that share your reflections on some of your section mates’ essays.

Your essay should address four questions in the context of the organization you choose:

  1. Why do you think the megatrend you selected is important to your organization’s management of process improvement and/or product development?
  2. What is the organization’s management doing to address this issue in the short term (the next two years) and the medium term (two to ten years out)?
  3. What other steps do you recommend the organization’s management take to address this issue in the short and medium terms?
  4. In the context of this organization, what are one or two important open questions related to this issue that you are unsure about that merit comments from your classmates?

Your essay should convey facts, analysis, and your recommendations. It should focus on a single organization (e.g., a single company, non-profit organization, or government agency) and a concern related to one megatrend. It is fine if the concern you choose relates to other megatrends that the organization is facing, but that’s not required. Roughly a third of your essay should be dedicated to each of the first three questions, with just a few sentences dedicated to the fourth question. Your essay should be at least 700 words but no more than 800 words, and must conclude with a word count in parentheses (such as 778 words).

When posting your essay to Open Knowledge, be sure to enter “Machine Learning”, “Additive Manufacturing”, or “Isolationism” in the Topics field.

More details on research, sourcing, deadlines, and other matters are provided in the RC TOM Challenge: 2018 note.  For assistance with the Open Knowledge platform during business hours (9:00 am – 5:00 pm M-F), email openknowledge@hbs.edu. A short video with instructions on how to post an essay to this platform is available at https://d3.harvard.edu/platform-rctom/how-to/.

Submitted (926)

Open Innovation at Nestle – Establishing an extended innovation ecosystem
Yaping
Last modified on November 12, 2018 at 5:31 pm
In a world of distributed knowledge and expertise, it's clear that open innovation has clear advantage across the value chain. This essay discussed the challenges of traditional in-house innovation model and why it is important for Nestle to use open [...]
Verizon: Battling crime through Machine Learning
tomchallenge
Last modified on November 13, 2018 at 3:16 pm
How Verizon is trying to predict and prevent crime by building smart cities
Safilo: 20/20 Vision, Or In Need of Better Sight?
Alicia I.
Posted on November 13, 2018 at 7:54 pm
Will a luxury eye manufacturer's vision to leverage 3D printing serve as a competitive advantage for the eyewear leader moving forward, or is the manufacturer at risk of falling victim to the buzz of a technology that is not congruent [...]
BHP Billiton: Productivity enhanced by machine learning in the mining industry
Gonzalo Eyzaguirre
Posted on November 13, 2018 at 6:22 pm
Mining is one of the first industries to start seeing a return on their early investments in machine learning. But why is artificial intelligence so important for this industry?
FEWER PILOTS IN THE COCKPIT—MORE OPPORTUNITIES FOR MACHINES
ATC
Posted on November 14, 2018 at 10:25 am
Looming worldwide pilot shortage opens doors for machine learning and other technical solutions.
Who Defines Beauty: Humans or Meitu?
Irene Kwok
Posted on November 11, 2018 at 6:18 pm
If you have the largest database of human portraits on the planet and each one is manually beautified, can you use machine learning to generalize beauty for the human race?
12 Things You Didn’t Know About BuzzFeed and Machine Learning
Berk Demarzo
Posted on November 13, 2018 at 6:03 pm
How BuzzFeed competes in a changing digital media landscape.
Power to the People: How the City of Boston is driving civic innovation through crowdsourcing
FLOlmsted
Last modified on November 12, 2018 at 10:18 pm
The public can help fill gaps in government capacity and drive newfound productivity - but only if the city has the means to turn data into action.
Bots with a Touch of Humanity
thunderfromdownunder
Last modified on November 13, 2018 at 1:43 pm
What Machine Learning Means to Automation Anywhere... Moving from Robotic to Intelligent Process Automation
Google Earth Engine: Organizing Geospatial Data to Save the Planet
Frasier
Last modified on November 13, 2018 at 7:24 pm
Google Earth Engine uses open access platform to develop content and applications to make their platform the dominant form in geospatial analysis
Neighborly: Leveraging Open Innovation to Spur Product Innovation in FinTech
I. Abbott
Posted on November 13, 2018 at 6:54 pm
Neighborly, the the kickstarter for municipal bonds, can leverage open innovation to develop new products and services to remain competitive and become an even more innovative market player.
The tension between people and data at Netflix
Hebarla-Halludba
Last modified on November 13, 2018 at 8:29 pm
Netflix is one the largest media companies in the world, growing from a small DVD rental company to a subscription-based streaming platform and media behemoth. In 2017, Netflix reported having over 117 million subscribers in more than 190 countries. Every [...]
Printer-to-Table: The Next Food Movement?
CL
Last modified on November 13, 2018 at 5:44 pm
Will 3-D food printers become the next household kitchen device?
Boeing: Additive Manufacturing Adding Enough?
Tristan Sansbury
Posted on November 13, 2018 at 7:52 pm
Boeing is a leader in implementing 3d printing processes on commercial airliners. But are they leveraging the benefits of 3d printing enough to reduce costs and manufacture more efficiently?
Can Amazon Use Machine Learning to Take On Fashion?
emch
Last modified on November 13, 2018 at 6:44 pm
Amazon is taking on the fashion industry by developing its own collection of private label brands.
Healthcare Social Networks: Can Crowdsourcing Patient-Reported Data Improve Outcomes?
PLM
Last modified on November 13, 2018 at 12:31 pm
  In the United States, fifteen new cases of ALS are discovered every day, an estimated 1 million people suffer from multiple sclerosis, and an estimated additional 1 million people suffer from Parkinson’s disease. [1] These are the three main [...]
Empire State of Minds: Open Innovation in NYC
Cardi V
Last modified on November 13, 2018 at 7:35 pm
The Big Apple is big on open innovation.
Printing Ideas: Innovating Ford’s Product Development Cycle through Additive Manufacturing
Allen Dorsey
Last modified on November 12, 2018 at 11:47 pm
How additive manufacturing (3D Printing) has become ingrained in Ford's product development cycle through rapid prototyping.
Future-Proofing Financial Services: Barclays Accelerator Program and Open Innovation
hbs51369394
Last modified on November 13, 2018 at 5:49 pm
“By accelerating the development of groundbreaking products and services, we know that we can help to keep Barclays at the cutting edge of financial services, all while helping to revolutionize the industry” - Michael Harte, Chief Operation and Technology Officer.
Capturing Value Through Machine Learning, Shell Adapts The Era of Low Oil Prices
Oguz Karatay
Last modified on November 13, 2018 at 1:08 pm
Exploring how Shell has leveraged machine learning to adapt the era of low oil prices through predictive maintenance, optimization and safety applications
John Deere: Betting the Farm on Machine Learning
MVM
Last modified on November 13, 2018 at 1:16 am
Deere's acquisition of Blue River Technology underscores its focus on using machine learning to improve agricultural efficiency
Lily Health – Scaling access to reproductive health advice with machine learning
Howard Roizen
Posted on November 8, 2018 at 7:24 pm
Introduction to Lily Health Lily Health is an early stage start-up in Nairobi, Kenya that provides women with sexual and reproductive health advice via mobile messaging. While there are a large number of companies that provide women’s health information and [...]
Ford Races Ahead in Additive Manufacturing
TOM199
Last modified on November 13, 2018 at 9:58 pm
Ford has a successful track record using additive manufacturing - and a bright future ahead, with industry-leading technology and high-potential options to explore
Football and Chess: How Machine Learning Can Improve Playcalling in the NFL
Derek R.
Posted on November 13, 2018 at 7:58 pm
Many fans and analysts liken American football to a game of chess. Each team strives to stay one step ahead of its opponents, and the team with more talented players can lose any game if their gameplan is poor. With [...]
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